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Array of cryogenic calorimeters to evaluate the spectral shape of forbidden $$\beta $$-decays: the ACCESS project

2023· article· en· W4378078470 on OpenAlexaff
L. Pagnanini, G. Benato, P. Carniti, E. Celi, D. Chiesa, Jacqueline Corbett, I. Dafinei, S. Di Domizio, P. C. F. Di Stefano, S. Ghislandi, C. Gotti, D. Helis, R. Knöbel, Joel Kostensalo, J. Kotila, S.S. Nagorny, G. Pessina, S. Pirro, S. Pozzi, A. Puiu, S. Quitadamo, M. Sisti, J. Suhonen, С. В. Кузнецов

Bibliographic record

VenueThe European Physical Journal Plus · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsQueen's University
FundersHORIZON EUROPE Marie Sklodowska-Curie ActionsAcademy of FinlandGran Sasso Science InstituteEuropean Commission
KeywordsBETA (programming language)PhysicsNuclear physicsCryogenic temperatureCryogenicsNuclear engineeringComputer scienceMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Abstract The ACCESS (Array of Cryogenic Calorimeters to Evaluate Spectral Shapes) project aims to establish a novel technique to perform precision measurements of forbidden $$\beta $$ β -decays, which can serve as an important benchmark for nuclear physics calculations and represent a significant background in astroparticle physics experiments. ACCESS will operate a pilot array of cryogenic calorimeters based on natural and doped crystals containing $$\beta $$ β -emitting radionuclides. In this way, natural (e.g. $$^{113}$$ 113 Cd and $$^{115}$$ 115 In) and synthetic isotopes (e.g. $$^{99}$$ 99 Tc) will be simultaneously measured with a common experimental technique. The array will also include further crystals optimised to disentangle the different background sources, thus reducing the systematic uncertainty. In this paper, we give an overview of the ACCESS research program, discussing a detector design study and promising results of $$^{115}$$ 115 In.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.340
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2023
Admission routes1
Has abstractyes

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